eval.py 文件源码

def rmse(Y_true, Y_pred):
    # https://www.kaggle.com/wiki/RootMeanSquaredError
    from sklearn.metrics import mean_squared_error
    print('shape:', Y_true.shape, Y_pred.shape)
    print("===RMSE===")
    # in
    RMSE = mean_squared_error(Y_true[:, 0].flatten(), Y_pred[:, 0].flatten())**0.5
    print('inflow: ', RMSE)
    # out
    if Y_true.shape[1] > 1:
        RMSE = mean_squared_error(Y_true[:, 1].flatten(), Y_pred[:, 1].flatten())**0.5
        print('outflow: ', RMSE)
    # new
    if Y_true.shape[1] > 2:
        RMSE = mean_squared_error(Y_true[:, 2].flatten(), Y_pred[:, 2].flatten())**0.5
        print('newflow: ', RMSE)
    # end
    if Y_true.shape[1] > 3:
        RMSE = mean_squared_error(Y_true[:, 3].flatten(), Y_pred[:, 3].flatten())**0.5
        print('endflow: ', RMSE)

    RMSE = mean_squared_error(Y_true.flatten(), Y_pred.flatten())**0.5
    print("total rmse: ", RMSE)
    print("===RMSE===")
    return RMSE